About
Hi! My name is Tony Liu, and I am a student at New York University's Courant Institute of Mathematical Sciences, currently pursuing a Bachelor of Arts degree in computer science with a minor in mathematics. I have always been fascinated by the boundless possibilities that computer science offers, and I am specifically interested in full stack development, artificial intelligence, natural langauge processing, and computer vision. Please scroll down to see the courses I have taken, my languages and skills, and my past projects. Please also feel free to check out my LinkedIn, GitHub, or write me an email. Links are below and on the side menu.
Experience
Software Engineer Intern
Black Creek Digital (June 2024 - Aug. 2024)
Contributed to the deployment of high-performance GPUs across various platforms to enhance cloud-based machine learning.
Developed Python and Bash automation scripts, leveraging Ansible for dynamic deployment of GPUs and automated platform switching.
NYU High Performance Computing Team Member
New York University (June 2023 - December 2023)
Member of the NYU HPC team, specifically the HPC Conjugate Gradient (HPCG) software group.
The HPCG benchmark uses a preconditioned conjugate gradient (PCG) algorithm to measure the performance of HPC platforms with respect to frequently observed but challenging patterns of computing, communication, and memory access.
Past Projects
Below are past projects I have done in many different languages. Feel free to check them out for yourself on my GitHub, linked on the bottom and side menu of my website.
GPU Marketplace Automation
Reduced GPU listing and delisting time by 40% by automating marketplace operations using Ansible playbooks and Python scripts, streamlining server setup, provisioning, and pricing adjustments. Optimized GPU search and price tracking by developing automated scripts to extract and analyze pricing trends, improving resource allocation efficiency for GPU providers.
AI-Driven Neural Network Caption Generator
Developed an artificial intelligence system in Python and PyTorch to autonomously generate text captions from image data, using the MNIST dataset. Constructed and monitored the integration of image feature extraction and dynamic caption generation, ensuring robust model performance using convolutional and recurrent neural networks. Implemented data preprocessing, model training, and evaluation processes, achieving a 97.78% accuracy rate on the MNIST test dataset with a convolutional neural network model.
Financial Tracker, MERN Stack
Managed a team of 5 developers to build a full-stack financial tracking app with MongoDB, Express, React, and Node.js, allowing users to add, edit, and monitor transactions, goals, and debts with real-time progress tracking. Implemented secure user authentication using JWT-based login/logout with token blacklisting, enhancing account security.
Full Stack Project - Recipe Rover
Designed and developed Recipe Rover, a dynamic full-stack web app, leveraging Node.js, Express, MongoDB, and Mongoose. Implemented user-friendly CRUD operations, secure authentication with Passport.js, and responsive UI using Handlebars. Implemented key security features, including user authentication, login/logout functionality, password encryption, flash messaging, and responsive views, maintaining a balanced blend of functionality and design appeal.
Translation Lookaside Buffer Translation (C Language)
Developed and implemented an automated Translation Lookaside Buffer (TLB) simulation program in C, capable of retrieving byte data based on virtual addresses. Developed functionality to read and store information about TLB contents, virtual page table, and physical memory cache. Created a user interface to prompt for virtual addresses, retrieving the corresponding byte data or displaying “Cannot be determined” if the data is unavailable. Ensured adherence to coding conventions, proper documentation, and memory management practices.
Trees on NYC Streets (Java)
Developed a console-based program leveraging open data from the NYC Department of Parks, parsing and analyzing a large tree dataset from the 2015 Street Tree Census. Utilized advanced programming techniques, including multi-file architecture, command line argument handling, and efficient data structures like lists and classes. Implemented a user-friendly interface for searching and retrieving tree species information, showcasing expertise in data processing, program design, and software development best practices.
Reverse Engineering (C / Assembly Language)
Implemented C code for multiple designated assembly functions, achieving functional parity with the provided version and passing rigorous testing.
Courses
Below are some relevant coursework I have completed / currently taking at NYU:
Software Engineering
Agile Software Development
Data Management and Analysis
Artificial Intelligence
Applied Internet Technology
Operating Systems
Basic Algorithms
Computer Systems Organization
Linear Algebra
Data Structures
Discrete Mathematics
Calculus II
Skills
I have extensive experience with the following languages: